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EffFeu Project: Towards Mission-Guided Application of Drones in Safety and Security Environments
Christopher-Eyk Hrabia1, Axel Hessler2, Yuan Xu3
1DAI-Labor, Technische Universität Berlin, Ernst-Reuter-Platz 7, 10587 Berlin, Germany. christopher-eyk.hrabia@dai-labor.de.
This research introduces EffFeu, an Unmanned Aerial System (UAS) for industrial firefighters, enabling autonomous control and object recognition. The goal is to reduce human cognitive load during critical rescue operations.
Area of Science:
- Robotics and Automation
- Artificial Intelligence
- Emergency Response Technologies
Background:
- Growing applications of Unmanned Aerial Systems (UAS) in rescue operations.
- Significant psychological and emotional load on human operators during critical situations.
- Need for integrated UAS solutions for industrial firefighters.
Purpose of the Study:
- To holistically integrate UAS into the daily workflow of industrial firefighters.
- To develop autonomous mission-guided control for Unmanned Aerial Vehicles (UAVs).
- To reduce the cognitive burden on human operators during rescue missions.
Main Methods:
- Development of an overall system architecture for UAS integration.
- Implementation of goal-oriented high-level task control.
- Comprehensive localization combining multiple approaches for GNSS-supported and GNSS-denied environments.
- Deep-learning-based object recognition for relevant entities.
Main Results:
- Conceptualization and current stage of the EffFeu research project.
- Demonstration of autonomous mission-guided control capabilities.
- Successful integration of localization techniques for varied environments.
- Initial evaluation results indicating system feasibility.
Conclusions:
- The EffFeu project aims to enhance industrial firefighting efficiency through autonomous UAS.
- The developed system addresses challenges in information analysis and human operator load.
- Further evaluation and development are ongoing to optimize UAS deployment in emergency response.
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